Overview
What is MLflow?
An open source machine learning platform for managing the complete ML lifecycle, developed at Databricks, that includes four components supporting experimentation, reproducibility, deployment, and a central model registry.
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Get StartedPricing
What is MLflow?
An open source machine learning platform for managing the complete ML lifecycle, developed at Databricks, that includes four components supporting experimentation, reproducibility, deployment, and a central model registry.
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Demos
Data & AI Tech Talk Ep.1 - 세션 2, [Demo] 아파치스파크, 델타레이크, mlflow
mlflow demo
Experiment Tracking Using MLflow in Machine Learning | Model Versioning & Model Registry | Part 1
Mlflow Open source framework Hermoine demo
Model Serving using MLFlow Model Registry | MLFlow 2.0.1 | Live Demo | Part 2 | Ashutosh Tripathi
MLflow Integration with PyCaret and PyTorch
Product Details
- About
- Tech Details
What is MLflow?
Use cases for MLflow include:
Generative AI
- Improve generative AI quality
- Build applications with prompt engineering
- Track progress during fine tuning
- Package and deploy models
- Securely host LLMs at scale with MLflow Deployments
Deep Learning
- Native integrations with popular DL frameworks (PyTorch, TensorFlow, Keras)
- Simple, low-code performance tracking with autologging
- UI for deep learning model analysis and comparison
Traditional Machine Learning
- End-to-end MLOps solution for traditional ML, including integrations with scikit-learn, XGBoost, and PySpark
- Simple, low-code performance tracking with autologging
- UI for model analysis and comparison
Evaluation
- Compare different ML models and GenAI application versions
- Evaluate different prompts
- Compare performance against a baseline to prevent regressions
- Simplify and automate performance evaluation
Model Management
- Package models for production, including code and dependencies
- Catalog, govern, and manage model versions
- Orchestrate model rollouts to staging and production
- Deploy models for large scale batch and real-time inference
MLflow Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
